In some cases, an enterprise might want to analyze, model, and/or predict performance values. For example, a business might want to predict a likelihood of a future event occurring based on a number of different factors. Typically, a user associated with the enterprise may manually define rules and/or logic to implement such predictions. These rules and/or logic can then be tested before being deployed for use by the enterprise. Such an approach, however, can be a time consuming and error-prone process—especially when the logic being implemented for an algorithm is complex and/or a substantial number of factors are associated with the prediction.
It would be desirable to provide systems and methods to accurately and efficiently facilitate predictive analytic algorithm deployment for an enterprise, while allowing for flexibility and effectiveness when creating, reviewing, and/or monitoring algorithms as appropriate.